NBA Connections
Introduction
Motivation
Our motivation for this project is to look at how connected NBA players are to each other through different levels of their career. We were interested in the idea of “the Seven Degrees of Kevin Bacon” and the possiblle application to the NBA. In a league with an average of ____ trades per year, players are seemingly very connected.
“Where players go to high school and college, along with who they played with there, greatly affects their chances of NBA success. Therefore, we want to offer our users the opportunity to explore this phenomena through an interactive network map that highlights these connections.”
Research Questions
- How connected are current NBA players?
- Is an early connection to NBA stars an indicator of career success?
Background
Background on Topic
Data Sources
basketball-reference.com !
Findings
Networks & Analyses
Conclusion
Limitations
Conclusion
References
Let’s clean up the format of that output:
| Speed | Distance |
|---|---|
| Min. : 4.0 | Min. : 2.00 |
| 1st Qu.:12.0 | 1st Qu.: 26.00 |
| Median :15.0 | Median : 36.00 |
| Mean :15.4 | Mean : 42.98 |
| 3rd Qu.:19.0 | 3rd Qu.: 56.00 |
| Max. :25.0 | Max. :120.00 |
In a study from the 1920s, fifty cars were used to see how the speed of the car and the distance taken to stop were related. Speeds ranged between 4 and 25 mph. Distances taken to stop ranged between 2 and 120 feet, with the middle 50% falling between 26 and 56 feet.
You can also embed plots as normal, for example:
Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.
